Distributed localization in wireless sensor networks The embedded Ubicom system 30 may 2002 Distributed localization in wireless sensor networks Koen Langendoen Niels Reijers Delft University of Technology The Netherlands

The embedded Ubicom system 30 may 2002 Technology trend Small integrated devices Smaller, cheaper, more powerful PDAs, mobile phones Many opportunities, and research areas Power management Distributed algorithms

Wireless sensor networks The embedded Ubicom system 30 may 2002 Wireless sensor networks Wireless sensor node power supply sensors embedded processor wireless link Many, cheap sensors wireless  easy to install intelligent  collaboration low-power  long lifetime

Possible applications The embedded Ubicom system 30 may 2002 Possible applications Fire rescue breadcrumbs exit path hazard detection Environmental monitoring detecting forest fires Monitoring bulk goods (potatoes) mix sensors with goods temperature, humidity

Required technologies The embedded Ubicom system 30 may 2002 Required technologies Efficient data routing ad-hoc network one or more ‘datasinks’ In-network data processing large amounts of raw data limited power and bandwidth Node localization

The embedded Ubicom system 30 may 2002 Ad-hoc localization Many nodes (> 100) NO infrastructure NO central processing Sparse anchor nodes known position Other nodes determine position using this data Distance measurement

The embedded Ubicom system 30 may 2002 Ad-hoc localization 2D, static node positions Several different algorithms have been proposed 3 will be compared Simulations on DAS2 supercomputer

The embedded Ubicom system 30 may 2002 Main result no ‘one size fits all’ Best algorithm depends on: error in range measurement (range variance) connectivity (number of neighbours) network topology node capabilities application requirements

The embedded Ubicom system 30 may 2002 Three-phase approach Determine distance to anchor nodes (communication) Establish position estimates (computation) Iteratively refine positions using additional range measurements (both)

Phase 1: Distance to anchor The embedded Ubicom system 30 may 2002 Phase 1: Distance to anchor Three algorithms Sum-dist [Savvides et al.] DV-Hop [Niculescu et al., Savarese et al.] Euclidean [Niculescu et al.] anchors flood network with their known position

The embedded Ubicom system 30 may 2002 Phase 1: Sum-dist Anchors flood network with known position Nodes add hop distances require range measurement B B: 6+4 = 10 6 4 C: 5+6+4 = 15 6 5 C A: 5 5 A

The embedded Ubicom system 30 may 2002 Phase 1: DV-hop Anchors flood network with known position flood network with avg hop distance Nodes count #hops to anchors multiply with avg hop distance A-B: 12 3 hops B avg hop: 4 3 2 4 1 C A

The embedded Ubicom system 30 may 2002 Phase 1: Euclidean Anchors flood network with known position Nodes determine distance by range measurement geometric calculation require range measurement B C A

The embedded Ubicom system 30 may 2002 Phase 1: Euclidean (2) Wanted: Distance A-G D G E Using AEGF: A-G = 8 ...or 3 F Using AEGD: A-G = 8 ...or 0.5 A A-G = 8

The embedded Ubicom system 30 may 2002 Phase 1: Euclidean (3) Needs high connectivity Error prone (selecting wrong distance) Perfect accuracy possible B D G E C F A

The embedded Ubicom system 30 may 2002 Phase 1: Comparison Range measurement Very accurate: Euclidean Reasonable: Sum-dist None / very bad: DV-hop

Phase 2: Determining position The embedded Ubicom system 30 may 2002 Phase 2: Determining position Two algorithms: Lateration very common local triangulation solve [Ax=b] Min-max [Savvides et al.] B C A

The embedded Ubicom system 30 may 2002 Phase 2: Min-max Using range to anchors to determine a bounding box Use center of box as position estimate B C A

Comparison: distance error The embedded Ubicom system 30 may 2002 Comparison: distance error

Comparison: distance bias The embedded Ubicom system 30 may 2002 Comparison: distance bias

The embedded Ubicom system 30 may 2002 A problem with Min-max Very sensitive to anchor placement

The embedded Ubicom system 30 may 2002 Phase 1 + 2 combined

The embedded Ubicom system 30 may 2002 Phase 1 + 2 combined Euclidean: very sensitive to both range variance and connectivity

The embedded Ubicom system 30 may 2002 Error and coverage There is a tradeoff between coverage and error

The embedded Ubicom system 30 may 2002 Matrix Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5 Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5 Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5 Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5 Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5 Radio range (connectivity) 16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1) Range variance Eucl Lat Sum-d MM DV-hop 0.025 0.05 0.1 0.25 0.5

The embedded Ubicom system 30 may 2002 Phases 1 and 2 Position error usually 30% of the radio range or higher Range measurements between nodes only used to determine anchor distance Can we do better?

Phase 3: Iterative refinement The embedded Ubicom system 30 may 2002 Phase 3: Iterative refinement obtain initial position (phases 1 and 2) broadcast my position iteratively refine position using: ranges to direct neighbours their initial positions

Phase 3: Iterative refinement The embedded Ubicom system 30 may 2002 Phase 3: Iterative refinement Initial estimate Receive neighbour positions Broadcast new position Local lateration A

The embedded Ubicom system 30 may 2002 Phase 3: Position error

The embedded Ubicom system 30 may 2002 Phase 3: Coverage

The embedded Ubicom system 30 may 2002 Conclusion No ‘one size fits all’ Refinement needs better coverage to be useful Lots of room for improvement in all phases Details in Tech Report PDS-2002-03 (http://pds.twi.tudelft.nl/reports/2002/PDS-2002-003)

The embedded Ubicom system 30 may 2002 What is wrong? Bad topology identical hop-TERRAIN positions twins Error propagation rapid infection of complete network – hop – triangulate – hop – triangulate –

The embedded Ubicom system 30 may 2002 Confidence weights Weight input for triangulation (wAx = wb) Initialization anchors 1.0 twins, identical hops 0 others 0.1 Triangulation large residue 0 small residue avg of input confidences